Analysis of Risk Factors for Intraoperative Bleeding in the Surgical Treatment of Cesarean Scar Pregnancy and Development of Predictive Models

Abstract

Xiao-Li Wan,1 Xu Wang,1 Zhi-Ping Feng,1 Xiao-Ling Zhou,1 Zhen-Wen Han,1 Jia-Mei Wu,1 Hong-Mei Xu,1 Ting Hu2 1Department of Gynaecology and Obstetrics, People’s Hospital of Leshan, Leshan, Sichuan, 614000, People’s Republic of China; 2Department of Gynaecological Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, Sichuan, 610041, People’s Republic of ChinaCorrespondence: Ting Hu, Department of Gynaecological Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, 55 Section 4, Renmin South Road, Chengdu, Sichuan, 610041, People’s Republic of China, Tel [phone], Email [email protected] Hong-Mei Xu, Department of Gynaecology and Obstetrics, People’s Hospital of Leshan, No. 238 of BaiTa Street, Shizhong District, Leshan, Sichuan, 614000, People’s Republic of China, Tel [phone], Email [email protected]: The objective of this study was to investigate the risk factors associated with cesarean scar pregnancy (CSP) and to develop a model for predicting intraoperative bleeding risk.Methods: We retrospectively analyzed the clinical data of 208 patients with CSP who were admitted to the People’s Hospital of Leshan between January 2018 and December 2022. Based on whether intraoperative bleeding was ≥ 200 mL, we categorized them into two groups for comparative analysis: the excessive bleeding group (n = 27) and the control group (n = 181). Identifying relevant factors, we constructed a prediction model and created a nomogram.Results: We observed that there were significant differences between the two groups in several parameters. These included the time of menstrual cessation (P = 0.002), maximum diameter of the gestational sac (P < 0.001), thickness of the myometrium at the uterine scar (P = 0.001), pre-treatment blood HCG levels (P = 0.016), and the grade of blood flow signals (P < 0.001). We consolidated the above data and constructed a clinical prediction model. The model exhibited favorable results in terms of predictive efficacy, discriminative ability (C-index = 0.894, specificity = 0.834, sensitivity = 0.852), calibration precision (mean absolute error = 0.018), and clinical decision-making utility, indicating its effectiveness.Conclusion: The clinical prediction model related to the risk of hemorrhage that we developed in this experiment can assist in the development of appropriate interventions and effectively improve patient prognosis.Keywords: cesarean section, prediction modeling, risk factors, uterine scar pregnancy

Keywords

• cesarean section
• prediction modeling
• risk factors
• uterine scar pregnancy